1. Field of the Invention
The invention relates to a palm biometric recognition method, more particularly to a palm biometric recognition method that is capable of effectively recognizing palms placed in various directions and at various angles.
2. Description of the Related Art
Palm recognition technique is one of the mainstream biometric identification techniques due to its relatively low cost and high identification rate.
In an article entitled “A biometric identification system based on eigenpalm and eigenfinger features” by Ribaric S., et al. and published in the “IEEE Transactions on Pattern Analysis and Machine Intelligence,” Vol. 27, No. 11 in November, 2005, there is proposed a biometric identification system by extracting eigenpalm and eigenfinger features from sub-images of palm and fingers. However, this prior art is not robust enough, especially in the condition that the palm in the image is inclined or when there are background illumination changes.
In an article entitled “Palm Line Extraction and Matching for Personal Authentication” by Wu., X., et al. and published in the “IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans,” Vol. 36, No. 5 in September 2006, there is proposed an approach for palm line extraction and matching with chaining coding. However, the coding method is too sensitive to the extracted palm lines.
In an article entitled “Hierarchical Identification of Palmprint using Line-based Hough Transform” by Li, F., et al. and an article entitled “A Hierarchical Palmprint Identification Method Using Hand Geometry and Grayscale Distribution Features” by Wu, J., et al., and both published in “The 18th International Conference on Pattern Recognition” in 2006, there are proposed two approaches for palmprint identification using hierarchical processing. However, these two approaches are too sensitive to the rotation and position of the palm in the image.
In an article entitled “An Adaptive Biometric System Based on Palm Texture Feature and LVQ Neural Network” by Ouyang, C.-S., et al. and published in “The Proceedings of 21st International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems”, 2006, there is proposed a more robust feature extraction and learning mechanism for palm biometric system. However, it has a limitation in that the rotation angle of the palm in the image cannot be more than 50 degrees.
Therefore, in order to alleviate the limitations of the prior art, there is the need for a palm feature extraction method and a palm biometric system that allow a user to scan his/her palm at any position and in any rotation conditions.